pith:UFNMQTM3
Judging the Judges: A Systematic Evaluation of Bias Mitigation Strategies in LLM-as-a-Judge Pipelines
Style bias dominates LLM judges at 0.76-0.92 strength across models, dwarfing position bias, while combined debiasing improves agreement for some judges by over 11 points.
arxiv:2604.23178 v2 · 2026-04-25 · cs.AI
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Claims
Style bias is the dominant bias (0.76-0.92 across all models), far exceeding position bias (<= 0.04), yet has received minimal research attention.
The chosen benchmarks (MT-Bench, LLMBar, and the custom set) and bias measurement protocols accurately isolate the targeted biases without introducing confounding artifacts from the test data itself or from how responses were generated.
Style bias dominates LLM-as-a-Judge systems far more than position bias, with debiasing strategies providing model-dependent gains and public tools released for replication.
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| First computed | 2026-06-25T01:18:38.181048Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
a15ac84d9b16632408496a804abf017d37fff889dd71edf862751ed24cb6be94
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/UFNMQTM3CZRSICCJNKAEVPYBPU \
| jq -c '.canonical_record' \
| python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: a15ac84d9b16632408496a804abf017d37fff889dd71edf862751ed24cb6be94
Canonical record JSON
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